Abstract by Bryce Hedelius

Personal Infomation

Presenter's Name

Bryce Hedelius

Degree Level


Abstract Infomation


Physics and Astronomy

Faculty Advisor

Dennis Della Corte


Protein Structure Prediction via Distance Mapping and Sequence Alignment


Although proteins are sequences of just 20 different amino acids, they are responsible for virtually every life sustaining-process. Proteins consistently fold the same way, but predicting the tertiary structure based on the sequence of amino acids remains one of the greatest unsolved problems in computational biochemistry. The state-of-the-art prediction method is a convolutional neural-network (CCN) produced by Google's Deepmind.


At BYU we are creating an improved prediction pipeline called ProSPr.  An initial step is the setup of databases to train a CNN.  Here we present our preliminary results and methodology in architecture and training of the CNN.